Energy systems are undergoing rapid transformation as sector coupling intensifies and variable renewable generation grows, creating a pressing need for flexible and transparent modeling tools. While many open-source frameworks offer rich features, extending them with new mathematical models typically requires writing custom software—a barrier for many analysts.

We present GEMS (Generic Energy Systems Modelling Scheme), a high-level modelling language designed to make multi-energy system adequacy and planning studies both more expressive and more accessible. GEMS brings model definitions out of the codebase and into simple YAML configuration files, where users describe variables, parameters, and constraints using natural mathematical expressions. These expressions are parsed into abstract syntax trees and automatically expanded—across time structures, scenario trees, and study data—into a complete optimization problem. This model-agnostic architecture enables rapid experimentation, lowers development and maintenance costs, and promotes true reusability: adding a new component requires no code, only data. The language is already supported in Antares Simulator and in the Python package GemsPy.

We present how GEMS could paves the way for interoperability between modelling tools, offering a neutral and extensible modeling layer that can be shared across the open-source energy modeling ecosystem.